Push grasping planner for cluttered environments

Submitted by Anonymous on Thu, 09/13/2012 - 11:22

Robots operating in our homes will inevitably be confronted with scenes that are congested, disorganized, and complex - or, simply put, cluttered. Consider, for example, a case where the robot must acquire an object from the back of a cluttered bookcase or refrigerator shelf. Reaching the target object from the top is impossible due to the constrained space inside the shelf; various obstacles block approaches from the front or side. Some of the obstacles are too large for the robot to grasp. The robot may even be uncertain about the poses of some objects. How can the robot complete the task?

During his internship at Willow Garage, Mehmet Dogar from Carnegie Mellon University worked on extending a method called "push-grasping" for operation in cluttered environments. When push-grasping, rather than directly closing its gripper, the robot can first "push" the target object along a linear path and into the gripper, an action primitive that is very robust to uncertainty in the object's pose.

In our novel implementation, the robot can make simultaneous contact with multiple objects in a deliberate and controlled fashion. This enables the robot to reach for and grasp the target while simultaneously moving aside obstacles in order to clear a desired path. We use a physics-based analysis of pushing to compute the motion of each object in the scene in response to a set of possible robot motions.

Rather than shying away from complex and sustained interactions with the world while grasping, robots can use these interactions to their advantage. Our planner utilizes pushing interactions to address clutter and uncertainty. This means robots can work more effectively in highly cluttered environments and succeed even if there is uncertainty about the poses of objects.